TY - GEN
T1 - Analysis-design-justification (ADJ)
T2 - 2021 IEEE Global Engineering Education Conference, EDUCON 2021
AU - Acuna, Ruben
AU - Bansal, Ajay
N1 - Publisher Copyright:
© 2021 IEEE.
PY - 2021/4/21
Y1 - 2021/4/21
N2 - We propose a new practice for the instruction of problem-solving skills: the Analysis-Design-Justification (ADJ) framework. The ADJ framework consists of learning outcomes which represent problem-solving skills, a type of problems to assess those outcomes, and a three-step process for problem-solving. Problems are open-ended and ill-defined, like those in the real world. Although there are several approaches to instructing problem-solving, ADJ supports a course environment with four specific requirements: established syllabi (ADJ may be added to a class already covering many topics), scale (ADJ can handle large classes), modality (ADJ can be performed synchronously and asynchronously), and heterogeneity (ADJ helps to provide scaffolding for diverse student populations). This framework takes inspiration from Polya's problem-solving process and uses the theoretical foundations underlying Problem-based Learning (PBL). The ADJ framework was enacted in the fall 2019 section of a Software Engineering (SE) class on operating-systems at Arizona State University (ASU). In the class, students were introduced to the ADJ framework through a series of group activities, and then asked to solve three ADJ problem sets. Students responded positively to use of the ADJ framework as both an instructional tool for class material, and to mature their problem-solving skills. However, some students had issues carrying out the ADJ process due to its focus on justification as opposed to constructing designs.
AB - We propose a new practice for the instruction of problem-solving skills: the Analysis-Design-Justification (ADJ) framework. The ADJ framework consists of learning outcomes which represent problem-solving skills, a type of problems to assess those outcomes, and a three-step process for problem-solving. Problems are open-ended and ill-defined, like those in the real world. Although there are several approaches to instructing problem-solving, ADJ supports a course environment with four specific requirements: established syllabi (ADJ may be added to a class already covering many topics), scale (ADJ can handle large classes), modality (ADJ can be performed synchronously and asynchronously), and heterogeneity (ADJ helps to provide scaffolding for diverse student populations). This framework takes inspiration from Polya's problem-solving process and uses the theoretical foundations underlying Problem-based Learning (PBL). The ADJ framework was enacted in the fall 2019 section of a Software Engineering (SE) class on operating-systems at Arizona State University (ASU). In the class, students were introduced to the ADJ framework through a series of group activities, and then asked to solve three ADJ problem sets. Students responded positively to use of the ADJ framework as both an instructional tool for class material, and to mature their problem-solving skills. However, some students had issues carrying out the ADJ process due to its focus on justification as opposed to constructing designs.
KW - Engineering education
KW - Operating-systems
KW - Problem-based learning
KW - Problem-solving
KW - Scalable instruction
KW - Software engineering
UR - http://www.scopus.com/inward/record.url?scp=85109037461&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85109037461&partnerID=8YFLogxK
U2 - 10.1109/EDUCON46332.2021.9454055
DO - 10.1109/EDUCON46332.2021.9454055
M3 - Conference contribution
AN - SCOPUS:85109037461
T3 - IEEE Global Engineering Education Conference, EDUCON
SP - 366
EP - 372
BT - Proceedings of the 2021 IEEE Global Engineering Education Conference, EDUCON 2021
A2 - Klinger, Thomas
A2 - Kollmitzer, Christian
A2 - Pester, Andreas
PB - IEEE Computer Society
Y2 - 21 April 2021 through 23 April 2021
ER -